How do you manage ERP data duplication?

1 Identify the root causes

To manage ERP data duplication, the first step is to identify the root causes. Analyze your data sources, data flows, data transformations, and data rules to discover where and why duplication occurs. Common causes of data duplication include lack of data standards and definitions, inconsistent data entry and validation, poor data integration and mapping, redundant data storage and backup, and human errors and fraud. Once you have identified the root causes, you can prioritize areas for improvement and prevent repeating the same mistakes.

2 Implement data deduplication tools

The second step to manage ERP data duplication is to implement data deduplication tools that can help you detect, remove, and prevent duplicate records in your ERP system. Data deduplication tools use various methods such as matching algorithms, fuzzy logic, rules-based logic, or machine learning to identify and resolve duplicate data. These tools can offer several benefits: automating and streamlining the data cleansing process, improving the data accuracy and completeness, reducing the data storage and maintenance costs, and enhancing the data security and compliance. Yet, data deduplication tools are not a one-size-fits-all solution; you still need to monitor and evaluate their performance and adjust their settings and parameters as needed.

3 Establish data governance policies

The third step to manage ERP data duplication is to establish data governance policies that can define and enforce the roles, responsibilities, standards, and procedures for managing data quality and integrity in your ERP system. These policies can help you align your data strategy with business goals and objectives, assign data ownership to the relevant stakeholders, create metrics and indicators to measure and improve data quality, implement quality controls and audits to ensure compliance and reliability, as well as educate and train staff on best practices and tools for data management. Ultimately, data governance policies can create a culture of data quality and excellence in your organization.

4 Leverage data quality services

The fourth step to manage ERP data duplication is to leverage data quality services that can provide expert guidance and support for your data quality and governance initiatives. These services offer a data quality assessment and diagnosis to identify and quantify any issues or opportunities, as well as data quality improvement and optimization to design and implement solutions and best practices. Additionally, they can provide data quality monitoring and maintenance for sustainability and scalability, as well as data quality training and education to enhance your skills and knowledge. By leveraging these services, you can benefit from the experience of professionals who can help you reach your goals.

5 Review and update your data regularly

The fifth step to manage ERP data duplication is to review and update your data regularly to ensure that it is current, relevant, and consistent. This means performing data quality checks and audits periodically to identify and correct any errors or anomalies. Additionally, you should implement data quality feedback and reporting mechanisms to collect and address any issues or concerns. Furthermore, you should update your data rules and standards as business needs and requirements change. Finally, archiving or deleting any obsolete or redundant data can free up space and resources. Ultimately, by reviewing and updating your data regularly, you can maintain and improve your data quality and governance over time.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?